Next Article in Journal
Forest Soil Cation Dynamics and Increases in Carbon on the Allegheny Plateau, PA, USA Following a Period of Strongly Declining Acid Deposition
Next Article in Special Issue
Single and Binary Fe- and Al-hydroxides Affect Potential Phosphorus Mobilization and Transfer from Pools of Different Availability
Previous Article in Journal
Undisturbed Soil Pedon under Birch Forest: Characterization of Microbiome in Genetic Horizons
Previous Article in Special Issue
Influence of Soil and Manure Management Practices on Surface Runoff Phosphorus and Nitrogen Loss in a Corn Silage Production System: A Paired Watershed Approach
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Phosphorus Transport along the Cropland–Riparian–Stream Continuum in Cold Climate Agroecosystems: A Review

1
USDA-ARS, Institute for Environmentally Integrated Dairy Management, Marshfield, WI 54449, USA
2
Department of Plant and Soil Science, University of Vermont, Burlington, VT 05405, USA
3
Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA
4
Department of Sustainable Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY 13201, USA
*
Author to whom correspondence should be addressed.
Soil Syst. 2021, 5(1), 15; https://doi.org/10.3390/soilsystems5010015
Submission received: 1 January 2021 / Revised: 4 March 2021 / Accepted: 5 March 2021 / Published: 9 March 2021

Abstract

:
Phosphorus (P) loss from cropland to ground and surface waters is a global concern. In cold climates (CCs), freeze–thaw cycles, snowmelt runoff events, and seasonally wet soils increase P loss potential while limiting P removal effectiveness of riparian buffer zones (RBZs) and other practices. While RBZs can help reduce particulate P transfer to streams, attenuation of dissolved P forms is more challenging. Moreover, P transport studies often focus on either cropland or RBZs exclusively rather than spanning the natural cropland–RBZ–stream gradient, defined here as the cropland–RBZ–stream continuum. Watershed P transport models and agronomic P site indices are commonly used to identify critical source areas; however, RBZ effects on P transport are usually not included. In addition, the coarse resolution of watershed P models may not capture finer-scale soil factors affecting P mobilization. It is clear that site microtopography and hydrology are closely linked and important drivers of P release and transport in overland flow. Combining light detection and ranging (LiDAR) based digital elevation models with P site indices and process-based models show promise for mapping and modeling P transport risk in cropland-RBZ areas; however, a better mechanistic understanding of processes controlling mobile P species across regions is needed. Broader predictive approaches integrating soil hydro-biogeochemical processes with real-time hydroclimatic data and risk assessment tools also hold promise for improving P transport risk assessment in CCs.

1. Introduction

Phosphorus (P) is an essential biosphere component and integral to cellular energy currency in the form of adenosine triphosphate. Phosphate molecules also form the backbone of deoxyribiose nucleic acid and other important biological molecules. In addition to imposing important limits on both terrestrial plant and crop productivity, P availability is also the main factor affecting freshwater eutrophication risk [1]. Unlike carbon (C) and nitrogen (N), P does not undergo substantial atmospheric loss. Phosphine (PH3) is the only known gaseous P form on Earth and its formation is not considered a substantial P loss mechanism from most soils or aquatic sediments [2]. In soil–water systems, pentavalent P forms appear to be most common (P5+); however, water-soluble reduced organic and inorganic P species have also been reported [3].
Once in solution, P acts as a weak Lewis acid with strong affinity for positively charged surface metal ligands, most notably aluminum (Al), iron (Fe), and manganese (Mn) hydroxides, often as organic matter-metal-P complexes [4,5]. Orthophosphate is bioavailable once in solution with maximum availability to (micro)organisms in soils and aquatic sediments near pH 7.0. Variably charged Al and Fe hydroxides are protonated at lower pH (and thus are highly soluble at lower pH), sorbing P from solution more efficiently [5]. As pH increases above 7.0, Ca and Mg phosphate formation is thermodynamically favorable; however, a range of metal-P species occur over a wide pH range in soils and sediments [4,5,6,7]. The term legacy P refers to accumulation of P in soils/sediments over time accelerated by anthropogenic activities including P inputs from agriculture. Part of the challenge in sustainable water quality improvement is that legacy P stocks can function as a variable but continual source of P release, hampering the efficacy of remediation efforts.
Agricultural P sources are a leading cause of water quality impairment in US rivers and lakes [8]. Managing P for the dual purpose of profitable agriculture and water quality is a major challenge and is pivotal in the water–energy–food security nexus [8,9,10,11]. Once viewed as relatively immobile and subject to mainly erosional transport, carrier-facilitated P transport as particulate or colloidal P in addition to dissolved P forms are all vulnerable to transport in Dunne and Hortonian overland flow (a.k.a., overland flow or surface runoff), interflow, subsurface tile drainage, and shallow groundwater flow [4,5,6,10,11,12,13,14,15,16,17,18,19,20]. Soil physical properties impose important physical transport constraints on P fluxes from upland agricultural and forested landscapes to riparian buffer zones (RBZs) and streams [15,17,18,19]. While overland flow is an important P transport mechanism in many settings, P is also mobilized in shallow subsurface flows where it has the potential to contribute P to open waters including ditches, streams, rivers, lakes, wetlands, and RBZs.
Cold climates characterize a large number of agriculturally productive regions globally and can be qualitatively defined by areas where a snowpack and frozen soils substantially influence hydrology [19]. Managing P transport in CCs is uniquely challenged by the combination of short growing seasons, high snowmelt runoff, and seasonally wet and/or partially frozen soils [20]. Recent literature highlights gaps in our current understanding of P transport in CCs, suggesting new approaches are needed to more effectively mitigate P transport from cropland to streams and better understand RBZs effects on P speciation and fluxes [21,22,23].
Water quality is intimately connected to the landscapes through which streams flow. RBZs are widely recognized for their stream water quality benefits, however, their impacts on P transport are variable and site-specific. Traditionally, P transport research has tended to focus on cropland or RBZs exclusively, with relatively few studies evaluating P dynamics in both cropland and RBZs and/or along their natural hydrologic gradients. Since RBZs and cropland often have a close hydrologic connection with similar processes regulating P transport, in this review we focus on factors influencing P transport in surface and subsurface runoff flows along the continuum from cropland through RBZs to streamflow, defined here as the cropland–RBZ–stream continuum. We primarily draw on studies from the USA and Canada over the last two decades.
Section 2 and Section 3 focus on the relationship among agronomic nutrient management, assessing agronomic P transport potential, and an overview of hydroclimatic and agricultural management factors influencing P transport. Section 4 and Section 5 discuss the critical source area concept and the importance of soil properties for P transport modeling, mapping and risk assessment. The cropland–RBZ–stream hydrologic continuum concept is introduced in Section 6, followed by a review of RBZ impacts on P transport in overland and subsurface flow (interflow and shallow groundwater), including a Section 7 describing stream bank erosion effects on P loading to streams. Section 8 concludes with future research suggestions and some examples from the literature illustrating new approaches combining hydrologic modeling with geographic information system tools for mapping runoff flow pathways in cropland–RBZ–stream systems.

2. Agricultural Nutrient Management

2.1. Agronomic Phosphorus Site Indices

Agricultural nutrient management plans (NMPs) specify the form, method, rate, and timing of crop nutrient applications with the goal of increasing crop nutrient use efficiency while minimizing environmental losses and crop production risk. In the US, regulated livestock farms must follow nutrient management guidelines developed by state Land Grant Universities and the USDA—Natural Resources Conservation Service (NRCS) (Figure 1). The amount of plant-available soil P (i.e., soil test P concentration) is a main driver of agronomic P recommendations. Unlike P, NMPs estimate plant-available N release from mineralization of soil organic matter, manure, and previous crops (using static rate estimates independent of in-season weather conditions). While NMPs account for total P inputs from manure applications, plant-available P release from mineralization of soil organic P is not considered. Similarly, while potentially ecologically important in some regions, atmospheric depositions of P (and N) are not considered.
Agronomic NMPs specify field-by-field crop nutrient needs and must include delineation of field characteristics related to erosion and nutrient loss potential, including modeled erosion estimates, presence of concentrated overland flow areas, and proximity to streams/ditches and other landscape features that affect water and nutrient movement (tile drains, karst topography, springs, swales, surface drain inlets). In general, these are also areas where manure and fertilizer P are not recommended during times of high runoff potential and, in some cases, are not to receive any further P applications. Watershed agencies may place further restrictions on land application of manure and fertilizer if farms are in priority watersheds with public drinking water supplies (i.e., New York City watershed, US Great Lakes, Lake Champlain).
Most NMPs in the US require a formal field site assessment of P loss potential using a research based, Land Grant University and NRCS-approved agronomic P site index (PSI). Agronomic PSIs include various rubrics for quantifying P source and transport factors to assign a P loss potential for individual fields based on soil and management factors [24] (Figure 1). Whereas some PSIs include more detailed runoff processes with calibration from edge-of-field runoff P data, many remain qualitative.
Recent US national guidance indicates that agronomic PSIs must establish threshold water quality risks to identify fields not to receive further P inputs. There is also a general consensus that, despite best efforts, P management practices are underperforming with respect to necessary water quality improvement and that there is a need to better account for site-specific hydrology, farm management, and biogeochemical processes influencing P fate and transport [10,11,19,22].

2.2. Precision Agriculture and Phosphorus Management

The ability to manage the timing and placement of crop nutrients in accordance with variable soil and weather conditions can help increase crop P uptake while minimizing losses in runoff. Precision agriculture takes advantage of known field spatial variability (from sampling) by using geographic information systems (GIS) to facilitate autonomous equipment navigation, real-time crop yield monitoring, and variable rate nutrient application. These tools also offer economic advantages for larger farms and are now fairly common [25]. Variable-rate fertilizer application technologies differentially apply P and other nutrients as soil and crop conditions vary across fields [26]. With variable rate application, auxiliary data important for P transport are also routinely collected including soil type boundaries, drainage features, erosion/runoff potential, and other spatially varying soil properties (soil test P, pH, organic matter content). These data can be used to refine P fertility for individual fields and used as inputs for PSIs and other P transport decision support tools aimed at better quantifying P transport potential.

3. Evaluating Cropland Phosphorus Transport Potential

3.1. Agricultural and Hydroclimatic Factors

Managing P inputs from manure and fertilizers for optimal crop production while protecting water quality is a challenge in CC agroecosystems. Livestock manure is an important source of C, N, and P for crops and has beneficial physicochemical effects on soil quality, however, P from manure can contribute to excessive soil P concentrations over time and can be readily transported by overland flow, particularly if not incorporated via tillage or injected beneath the soil surface [27,28,29]. Dairy manure contains relatively high P content with speciation and total P content dependent on animal species, age, diet, and other farm-specific factors [29]. However, once applied to soils, research indicates that much of the organic P transforms fairly rapidly to inorganic P [30,31] and subject to transport in runoff [10,18,20,22]. Recent research suggests that dairy manure application can be associated with larger and more variable overland flow P losses compared to fields receiving similar rates of fertilizer P [32].
It is clear that a range of P forms can be transported in both overland and shallow subsurface flow in a variety of crop production systems receiving a mix of fertilizer and organic P mainly in the form of livestock manure [5,10,12,13,14,15,16,17,18,19,20,21,22,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49]. While agricultural operations often account for a major nonpoint P source in the watershed via the combination of land disturbance and P applications, it is also important to recognize that streambank erosion and runoff from forested lands can contribute to loading to streams [50,51,52,53]. Irrespective of original source, landscape position, or form, P transfer risk to streams is greater during the non-growing season, when much of the annual runoff occurs in CC regions [15,18,19,20,21,22,34,35,45,46,47,52,54,55,56,57,58,59,60]. Biogeochemical reactions removing P from solution (sorption and plant and microbial assimilation) also diminish during the non-growing season, contributing to greater overall P mobility and the non-growing season is also a period of elevated overland flow potential. Frozen surface soil layers all but eliminate surface water infiltration and exacerbate overland flows during snow melting or mixed precipitation events. Additionally, decreased soil–water interaction in frozen or partially frozen soils contributes to lower P sorption and greater P mobility in overland flow compared to unfrozen soils. On the other hand, when soils are not frozen and infiltration is possible, greater soil–water interaction increases P removal from solution via sorption reactions and metabolic uptake prior to overland flow reaching streamflow.
Climate and the amount, form, and intensity of precipitation are important factors affecting overland flow, erosion, and P transport potential, and varies regionally in CCs. Hoffman et al. [35] monitored overland flow from five small agricultural watersheds (4 to 30 ha) over a 12-yr period in southwestern Wisconsin (WI) and showed that mixed precipitation events had greater mean dissolved reactive P (DRP; assumed to be mainly orthophosphate and bioavailable) concentrations (2.2 mg L−1) than snow (1.9 mg L−1) or rainfall events (1.2 mg L−1). They also reported that snow (74%) and mixed (84%) events had nearly two-fold greater proportions of DRP in overland flow compared to rainfall (39%), stressing the importance of field-specific interactions among precipitation types and soil physical conditions, temperature, and depth of frozen layers.
Vadas et al. [54] used 108 site years of edge-of-field overland flow data from WI and a calibrated P transport model (SurPhos) to evaluate P loss potential with differing soil hydrologic and P management. Unlike many current P transport models, SurPhos attempts to simulate snowmelt runoff dynamics and processes regulating DRP transfer from soil, fertilizer, and manure P sources using daily weather data. Their simulations indicated site hydrology was the overriding factor influencing P loss with winter application increasing P loss potential by 2.5 to 3.6 times relative to unfrozen soils. They reported that P loss potential was greatest in late January and early February (from melting events) and that P loss potential was reduced by a factor of 3.4 to 7.5-fold by applying manure to fields with a lower overland flow potential.
In a similar geographic region, Zopp et al. [60] used regression tree analysis to determine factors affecting flow-weighted mean total P (TP) and dissolved P concentrations/loads in the upper Midwest using a large regional edge-of-field overland flow and P export data set from WI and Minnesota with 26 fields, 123 site-yr of data, and >20 additional hydroclimatic and management variables. They reported that, when soils were frozen, the majority of overland flow TP was dissolved. Overall, labile soil P concentration at 0–5 cm was the most important predictor of flow weighted mean TP and DRP concentrations in frozen conditions. Soil labile P content is often highly correlated with overland runoff flow DRP concentrations [61] and a critical input for P transport models and PSIs. Additionally, recent edge-of-field runoff research suggests that surface soil P concentration is a main factor affecting DRP transfer to overland flows [62,63], emphasizing the need for NMP strategies to consider practices that slow down the rate of P accumulation in surface soils in addition to focusing on applying manure/fertilizer to fields under low P loss risk conditions (i.e., when soils are unfrozen).

3.2. Cropping System Impacts on Phosphorus Loss Potential

Soil erosion and total P loss in overland runoff flows are both generally greater under annually tilled crops compared to perennial forage crops or pasture due to mechanical disturbance of tillage operations and lack of continuous vegetative cover [55]. Despite this effect, dissolved P loss can still be substantial in overland flow from perennial forage and no-till systems due to P accumulation in surface soils [55,56]. On the other hand, in annually tilled systems, there is a wide range of impacts on erosion, overland flow, and P loss potential. Besides greater aeration and other potential agronomic benefits, tillage can decrease overland runoff flows compared to no-till by increasing surface roughness in finer-textured soils [57,58,59]. While there are well-known tradeoffs between greater erosion/particulate P loss with tillage versus lower erosion/particulate P loss with no-till, it is important to note that in some soils, tillage can decrease overland runoff potential, however, this effect is site-specific and depends on several other variables including the consistency and duration of no-till practices. Pasture land often comprises a substantial fraction of agricultural land and generally results in less erosion and particulate P transport compared to row crops; dissolved P forms can still be vulnerable to transport in overland flow (see Section 4, Section 5 and Section 7 for more discussion). While beyond the scope of this review, it is important to recognize that pastured livestock with direct stream access can pose serious water quality challenges [55].

4. Critical Source Areas of Phosphorus

Source and Transport Factors

The critical source area concept assumes P transport potential is a function of hydrologic loss mechanisms interacting with P sources on the landscape at any given time [22,32]. Agricultural P sources subject to transfer in runoff pathways and streams along the cropland–RBZ–stream continuum include soil, manure, and fertilizer. From a watershed biogeochemical perspective, RBZ sources must also be considered as potential P sources to streams in the form of overland and subsurface flows or via stream bank erosion [50,51,52,53]. Determining where and when P sources interact with hydrologic flow paths to physically transfer P to RBZs and streamflow is integral to critical source area and watershed “hotspot/hot moment” approaches and derives from distributed hydrologic modeling theory, now more commonly known as variable source area hydrology [64,65,66,67]. Variable source area hydrology posits that the amount and timing of overland flows are driven by topographic and soil moisture gradients [66,67,68,69,70]. Studies indicate that incorporating variable source area hydrology routines into watershed P transport models show promise for improving overland runoff flow P fluxes [15,22,32,66,67,68,69,70]. Overland flow sources to streamflow include cropland areas but also near-stream areas subject to variable soil moisture regimes and overland flow generation (i.e., RBZs, swales, springs/seeps, and other wetlands) [68,70,71]. Since topographic features are an important control on both overland flow generation and groundwater hydrology, accurate characterization of cropland–RBZ–stream topographic complexity is critical for developing realistic models and indices of P transport that can better account for RBZs impacts on P transport.
Both spring snowmelt and storm events are important times for P transfer from cropland to surface waters and from variable sources areas to streams [10,14,18,32,35]. Part of the difficulty of controlling CC cropland P transport resides in the seasonal asymmetry between greater non-growing season runoff potential and concomitant decreased P sorption potential and biological assimilation driven by lower soil temperatures, effectively increasing dissolved P availability to overland flow. Recognizing this asymmetry between elevated runoff potential and diminished P removal capacity is a critical aspect for NMPs to consider in CC regions to better manage cropland P loss risk and more effectively target P-specific best practices for mitigating P transport to streams.

5. Importance of Soil Properties for Evaluating Phosphorus Transport Potential

Modeling and Mapping

GIS tools and digital soil survey data are routinely used in agriculture to develop NMPs and to support other agronomic and environmental objectives. These tools can help identify and manage soil-related factors affecting crop yields while providing important input data for P transport risk assessment tools [72,73,74]. For example, digital elevation models (DEMs) are routinely used in P transport models and PSIs for estimating field slopes for erosion assessment. Agronomic PSIs and several P transport models [Agricultural Policy/Environmental eXtender Model (APEX); Environmental Policy Integrated Climate (EPIC) model; Soil and Water Assessment Tool (SWAT); Surface Runoff Phosphorus Model (SurPhos)] use soil survey data or measured properties as model inputs [22,32,54,59,69,70,75,76]. Riparian biogeochemical models including the Riparian Ecosystem Management Model (REMM) and RZ-TRADEOFF also use soil survey data [77,78,79,80].
While soil survey maps are useful for many applications, it is important to note that a number of them were performed in the 1960 and 1970′s. The maps were also done using different methods and mapping scales. Early mapping focused on agricultural areas with less emphasis on forested and stream areas in general. A soil survey conducted at 1:20,000 scale (a fairly representative soil survey scale) generally relates to a minimum mapping area (termed ‘mapping unit area’ by USDA-NRCS) of approximately 1.2 ha, implying variation <1.2 ha cannot be included. Thus, soil variation may or may not be reflected at a given map scale depending on a given objective. Moreover, US soil surveys operate on the general assumption that up to 15% of any soil series may be comprised of a taxonomically distinct series.
Modern soil survey mapping techniques can integrate traditional soil survey field data with a range of computational tools to predict soil associations (using classification, fuzzy logic, generalized linear modeling, geostatistics, neural networks, regression trees, machine learning/artificial intelligence algorithms and hybrid models) [81,82]. These approaches are collectively aimed at improving digital soil mapping precision with the ability to integrate expert knowledge and prediction uncertainty [81,82]. Light detection and ranging (LiDAR) derived DEMs can provide detailed microtopographic information to help map soils and overland and subsurface hydrologic flow pathways. A few recent studies have used LiDAR-derived DEMs with hydrologic modeling to design variable-width RBZs based on landscape attributes to optimize agricultural land efficiency and stream water quality protection [71,82,83,84,85]. Given the strong association between soils, water movement and P biogeochemistry, characterization of soil hydrology and properties affecting P desorption potential (pH, redox, labile P status) is paramount for better understanding and predicting P fate and transport in CC cropland–RBZ–stream environments.

6. Cropland–Riparian–Stream Hydrologic Continuum

Hydrologic processes are important for understanding the relative contribution of different P sources to watersheds and the relative effectiveness of P transport mitigation practices such as RBZs [15,16,17,18,19,20,21,22,38,39,40,41,42,43,44,45,46,47,48,49,69,75,86,87,88,89,90,91]. Site hydrology is also critical for P transport from cropland to RBZs and from RBZs to streamflow. We define the cropland–RBZ–stream continuum as the contiguous land area between active cropland (including pastures) and the nearest perennial or intermittent stream capable of transporting P to downstream systems. Runoff pathways along the cropland–RBZ–stream continuum contributing to streamflow (Qsf) include Hortonian and Dunne overland flow (Qof), groundwater flow (Qgw), and interflow (Qif) (Figure 2). Subsurface tile drainage is a fairly common practice for farms in CCs with poorly drained soils to improve agronomic performance. Tile drain flows are a mix of shallow groundwater and vadose zone water fluxes. Since tile drainage represents a form of subsurface lateral flow, it is included with Qif for simplicity. Stream flow (Qsf) at any given time is thus the sum of individual flow components:
Qsf = Qof + Qif + Qgw
Note that groundwater flow components (Qgw) are lumped for simplicity and likely include a mix of both shallow/younger and deeper/older flow paths. Stream baseflow is defined as those times when Qgw is the main flow source contributing to Qsf. Interflow (Qif) includes infiltrated water subject to gravitationally driven lateral movement in the unsaturated zone often induced by the presence of a flow boundary. To reiterate, the uncultivated area between cropland edge-of-field areas and stream bank edges is defined as the RBZ (Figure 2).
RBZs include both semi-natural and unmanaged systems in addition to designed and well managed RBZs. The critical assumption is that RBZs must have permanent vegetation maintained with no agricultural operations (i.e., no tillage or agrichemical applications) occurring. Riparian areas are largely owned and managed by farms in the US and exist in a wide range of field conditions. The grass buffer in Figure 2 is approximately 2 to 3 m wide, which is narrow relative to NRCS riparian forest buffer specifications (minimum width = 10.7 m). Maintaining minimum width RBZs is mandatory in some US states. For example, in Vermont, State Required Agricultural Practices mandate a 3 m permanent RBZ along drainage ditches and 7.6 m wide RBZ along perennial streams and lakes.

7. Riparian Buffer Zone Impacts on Phosphorus Transport

7.1. Phosphorus Transport in Surface Runoff (Qof)

Overland flow is an important P transport pathway in cropland as previously highlighted and also critical for P transport in RBZs, along with subsurface components (Figure 3). Properly maintained RBZs can contribute to improved stream water quality and other ecosystem benefits including fish habitat and biodiversity [73,92,93]. Research also indicates RBZs of varying width and composition can attenuate sediment and P fluxes in Qof from upland agricultural areas [38,64,76,78,79,82,83,85,86,92]. In general, a curvilinear relationship is found between RBZ width and TP removal in Qof; however, RBZ width impacts on dissolved P fluxes are less clear. Research also indicates RBZ effects on dissolved P are more variable, with several studies noting dissolved P increases in RBZs [37,78,86,92,94,95,96,97]. Fixed width RBZs may not be the most efficient for mitigating P since landscape heterogeneity plays an important role in both cropland P loss and RBZ-P attenuation potential [82,86,87,88,89,90,94,97]. While RBZ width is an important consideration, other factors can have equal or greater importance on P transport from cropland to RBZs [75,76,77,78,79,86,87,88,89,90,91,92,94,95,96,97,98,99,100].
Adequately controlling dissolved and particle-bound P species in Qof is a challenge in both agricultural fields and RBZs. Kieta et al. [94] reported wide variation in P removal efficiencies (from −36% to +89%) for vegetated buffer strips and concluded that both soil P accumulation and freeze–thaw cycle effects on P release from vegetation were important variables related to P removal effectiveness in Qof. They emphasized the difficulty in using vegetated buffers to control P transport in CC agroecosystems where frozen soils and snowmelt-runoff processes limit soluble P removal in Qof, compared to warmer climates where plants and soils remain more biologically active in the non-growing season.
In a review of 41 field studies of crop biomass residue effects on P transport in cropland Qof conducted in CC regions, Liu et al. [98] reported wide ranging biomass P concentrations with substantial P inputs in some cases (0.03 to 51.7 kg P ha−1); however, 45 to >99% of P was retained by soil. Fields with lower erosion potential and biomass residue tended to increase DRP concentrations in Qof compared to fields without residue, suggesting that biomass itself or the interaction of biomass residues with soils increased net P flux to Qof. A similar process may operate in RBZ soils dominated by grass species, whereby a portion of organic P from vegetation and roots is recycled and contributes to the labile inorganic P pool. Labile soil P concentration modified crop residue effects on P transport; fields with lower soil test P and presumably greater sorption capacity tended to retain a greater fraction of P released compared to fields with higher soil P [98]. Beyond highlighting the importance of crop residue effects on P mobilization, these results support the idea that labile soil P concentration is a critical factor affecting P release to Qof in both cropland and RBZs [100,101,102,103,104,105].
The combination of permanent vegetation and little disturbance in RBZs tends to result in net organic C and P accumulation [86,87,88,89,90,94,97]. Likewise, forest and long-term grassland soils often display organic C and P stratification with enriched surface layers. Dissolved inorganic P in Oof is important since it is immediately bioavailable; however, a substantial fraction of P in overland and subsurface flows can be organic in all of these systems [23,45,86,103,104,105]. Bol et al. [23] reviewed P fluxes in temperate forested ecosystems and reported total soil solution P concentrations of 1 to 400 µg P L−1. Dissolved organic P was the main form, mainly composed of orthophosphate monoesters (phytic acid and its degradation productions). Both labile and more strongly sorbed organic P forms can also be important in RBZ soils. Young et al. [104] reported that 78% of the mean water-extractable total P in surface RBZ soils was organic, nearly half of which was hydrolyzed to DRP after phosphatase enzyme addition, suggesting a substantial fraction of water-soluble organic P in Qof could be bioavailable [104].
Strong linkages between soil C and P biogeochemical cycling have long been recognized by pedology and forest soils literature [106,107,108,109,110], however, as highlighted by Bol [23], little progress has been made on developing a quantitative framework to move static P measures. Dissolved and particle-bound organic P are covalently bound to C and partially account for correlations between soil C and P, however, organic C and other factors like pH and redox potential alters inorganic P solubility and orthophosphate sorption/desorption dynamics [104,111]. Several studies report significant correlations between labile soil inorganic P availability and soil organic C attributing the effect to dissolved organic C competing for P sorption sites [4,5,86,87,88,103,104,110]. It is well known that carboxylic acid (R-COOH; where R = an alkyl group) and other organic acids compete for P binding sites on soil surfaces after oxidation to carboxylate (COO), which is difficult to disentangle from inherent correlations between C and P. A certain fraction of organic P is also dynamically hydrolyzed to inorganic P, further confounding relations between C and P.

7.2. Streambank Erosion and P Loading to Streamflow

Streambank erosion is another potentially important P contributor to Qsf with implications for legacy P transport in fluvial systems, aquatic P biogeochemistry and water quality [50,51,52,53,89,112]. Ishee et al. [51] combined GIS imagery and field sampling to track streambank erosion rates with field soil P analyses (n = 76 sites) to estimate P inputs from streambank erosion over a 4-yr period. Approximately 6 to 30 % of the total P loading to Qsf among sites was due to streambank erosion. The authors hypothesized that eroding streambanks could act as a sink for P since labile P concentrations were low compared to agricultural land uses. In the Mad River basin of Vermont (a subwatershed of Lake Champlain), Ross et al. [53] used aerial imagery and post-storm sampling to estimate P loading from Tropical Storm Irene in 2011. An area from six sites (0.87-km length of stream bank) contributed an estimated 17.6 × 103 Mg of sediment and 15.8 Mg of total P, similar to average annual watershed P export. Substantial streambank erosion and P loading has also been documented in the Midwestern US. Zaimes et al. [112] measured streambank erosion and associated P loads along forest RBZs, grass dominated buffers, pasture (stratified by continuous, rotational, and intensive rotational) and row-cropped fields for three distinct physiographic regions in Iowa where grazing is common. Forested RBZs had the lowest streambank erosion and P loss rates (2 to 6 kg P km−1 year−1), followed by grass RBZs (9 to 15 kg km−1 year−1). The greatest P loading rates were associated with pasture (range: 37 to 123 km−1 year−1) and row-cropped fields (108 kg km−1 year−1).
Collectively, results indicate that high P loading rates from streambank erosion can overwhelm TP loss inputs to Qsf compared to other sources. Increased Qsf from greater precipitation extremes related to climate change along with land use/cover effects (ie., tile drainage/ditching cultivation of native prairie and wetlands) have also contributed to greater runoff flows to Qsf and exacerbated nutrient loss [113,114,115]. For example, riverbank sediments were reported to be the major P source for the Lake Pepin sediment P pool before 1850, which then switched to both a source and carrier of anthropogenic P after European settlements in 1850 [50]. Similarly, sediment–bound P from streambank erosion and river sediment fluxes to coastal estuaries can be a net P source under steady state conditions with the extent of P desorption related to changes in pH and redox potential [48,49,52,116]. These and other studies indicate that streambank erosion itself can be an important P source to Qsf compared to other sources, particularly if widespread throughout the watershed. However, whether or not these sediments ultimately act as a DRP source or sink is inherently dynamic and difficult to predict given the array of watershed scale land use management and variables influencing watershed P speciation and fluxes [10,11,19,22,23,38,40,42,43,44,66,69,75,86,94,115].
Using high frequency monitoring of Qsf in two predominately forested watersheds of the Piedmont physiographic region in Maryland, USA, Inamdar et al. [52] showed winter storms after freeze–thaw cycles exported high loads of suspended sediment and particulate C and N, with peak suspended sediment and particulate N concentrations >5000 mg L−1 and >15 mg L−1. Based on their data and observations from other USGS monitoring stations, the authors speculated that much of the Qsf sediment was derived from streambank erosion and fluvial sources. Inamdar et al. [116] sampled streambank legacy sediments in the Chesapeake Bay watershed, USA, along with upland soils, and evaluated P release potential using laboratory based measures with reducing and oxidizing conditions. Streambank legacy sediments had low average labile P concentrations and equilibrium P concentrations and might therefore act as a net P sink; however, sediments incubated under reducing conditions had nearly 5-fold greater DRP concentrations, suggesting legacy sediments could readily desorb P to Qsf under conditions of low redox potential due to dissolution of Fe-P compounds. The authors highlighted the need for P transport models and indices to better account for spatially variable P legacy sediment impacts on aquatic ecosystems. In summary, while it is apparent that streambank erosion and fluvial transport of legacy sediments can contribute P to Qsf, the relative water quality risk for downstream open waters depends on the amount, speciation and timing of P fluxes relative to other P sources, in addition to sediment characteristics (i.e, labile P content/speciation, P sorption capacity, pH, organic C) and biogeochemical changes in differing RBZ soil and Qsf environments.

7.3. Riparian Zone Impacts on Subsurface Phosphorus Transport (Qif and Qgw)

While there is considerable RBZ-P attenuation uncertainty surrounding Qof, there is wider variation for shallow groundwater and vadose zone P attenuation [86,99]. Despite the fact that RBZs are commonly recommended for reducing P transport, information on RBZ effects on P speciation and fluxes is lacking, particularly in CC regions where hydro-biogeochemical processes and agricultural/riparian management interactions largely control nutrient fluxes [94,99]. Moreover, the hydrologic and soil processes driving P transport from upland agricultural areas to RBZs and Qsf are themselves highly spatially and temporally variable, particularly during freeze–thaw cycles with diurnally fluctuating air temperatures and soil physical conditions (frozen/partially frozen) that complicate water infiltration, subsurface water movement, and therefore P transport [45,46,47,52,91,94,99,105,116]. An improved understanding of coupled soil hydro-biogeochemical processes driving P transport from RBZs to Qsf in CC regions is needed, in addition to developing a broader set of predictive tools that can accommodate the multivariate and dynamic nature of subsurface P transport and subsequent movement and potential transfer to Qsf.
Hydrology, soils and vegetation are intimately linked and their interactions largely control localized physicochemical environments and biogeochemical mechanisms regulating P availability to both matrix and macropore soil water flows [117,118] (Figure 3). This observation helps partially explain studies reporting mixed efficacy for RBZ subsurface P attenuation [13,37,78,86,95,96,117,118,119,120,121,122,123,124]. In shallow Qgw of RBZs from eastern Canada, Carlyle and Hill [95] reported that RBZ shallow Qgw with lower dissolved oxygen concentrations had higher ferrous iron (Fe2+) and DRP concentrations, and suggested that Qgw redox potential was a main factor affecting the likelihood of P release to Qgw and discharging Qsf. Young and Briggs [13] monitored P concentrations in soil solution (sampled via tension lysimeters, representing Qif) and shallow Qgw for 16 paired cropland-RBZ plots for >2-yr in Central New York. Mean DRP concentrations in Qgw and Qif were lower for RBZs compared to corn and hayfields; however, poorly drained RBZs had greater particulate reactive and dissolved unreactive P concentrations in Qgw, suggesting poorly drained RBZs with elevated water tables and low to moderate labile P status were vulnerable to P release and transport in Qgw compared to more oxidizing Qgw zones. The importance of soil hydrology on P biogeochemistry was also supported by ammonium and nitrate-N patterns. Shallow Qgw zones with lower dissolved oxygen concentrations had lower nitrate-N, higher ammonium-N, and significantly greater DRP concentrations, which suggests denitrification zones could be episodic P flux hotspots [13,125].
Gu et al. [126] combined Qgw, Qif, and Qof measures in the Kervidy-Naizin catchment of Northwestern France over 4-yr with P concentrations and speciation to elucidate transport mechanisms in shallow subsurface flows (Qif + Qgw). The authors hypothesized that the main P transport mechanisms were related to soil hydrology via: (i) reductive dissolution of ferric (Fe3+) phosphates during episodic saturation events (hot moment) and, (ii) P mobilization in soil water flows associated with rainfall events following dry periods (hot moment). The degree and duration of soil saturation is a critical factor affecting P release from RBZ soils since prolonged saturation can elicit both reductive dissolution of Fe-P and Mn-P compounds and encourages dissolution of Al-P, Ca-P, and other P complexes [86,87,111,127,128]. Changes in pH during saturation also affect release of dissolved organic P and other C-P complexes that may be more vulnerable to movement in Qif and/or Qgw due to lower affinity for P sorption sites compared to free orthophosphate [4,5,13,37,78,86,103,104,111,116,117,118,127,128]. Shallow Qgw residence time is also an important factor influencing thermodynamic conditions and P release and retention in RBZs, particularly via the Fe-P redox cycle [86,111].

7.4. Artificial Subsurface Tile Drainage and Phosphorus Loss Potential

Installation of subsurface agricultural tile drainage systems (a.k.a., tile drains) is relatively common in CC agricultural regions with poorly drained soils [129]. Modern tile drainage systems consist of perforated plastic drainpipe (typically 10 cm ID for lateral field lines) typically installed at a depth of 1.0 to 1.5 m deep with variable lateral spacing and designs. Hydrologically, the main objective is lowering the seasonally high ground water table elevation, which facilitates more rapid gravitational (macropore) soil water drainage compared to an undrained condition in a similar setting. Tile drains have long been recognized for their multiple agronomic benefits (e.g., greater yields, earlier planting/harvesting) and erosion mitigation potential [36,129]. Typically, tile-drained fields outlet to some type of surface ditch or directly to streams or open waters.
While accelerated nitrate-N loss via tile drainage flows has long been recognized, P leaching and transport in tile systems has gained more attention over the last two decades [12,16,36,45,63,105]. In a recent review, King et al. [36] discuss P transport dynamics in tile drained systems and the role of soil and nutrient management factors in controlling P concentrations and fluxes to tile drained soils (mainly the US and Canada). In addition to preventing soil P accumulation to high or excessive levels, the authors stressed the importance of soil type and the propensity for macropore flow in regulating P movement to tile drain flow. Unlike matrix soil water flow characterized by advection and dispersion mechanisms, macropore flow is much more rapid, decreasing the opportunity for P sorption reactions that might otherwise bind P and reduce transfer potential to tile flows [12,16,36,41,130].
While P leaching and transport to tile flow is a concern in some settings, it is also important to recognize that tile drains in general significantly reduce Qof and as such can mitigate particulate and/or DRP transport in Qof compared to undrained conditions in some settings [12,36,45,105]. From this standpoint, tile drains are part of the set of solutions to help mitigate P transport in Qof using combinations of practices, while also potentially contributing to less P transfer to down-slope RBZs [131]. Therefore, while not considered environmentally beneficial with respect to N, tile drains may offer site-specific benefits for reducing erosion, Qof, and P transport in Qof. Early RBZ research with N suggested tile drains could lower the water table sufficiently to reduce interaction of cropland Qgw with upper RBZ soil horizons, thus contributing to lower nitrate-N attenuation in the RBZ. However, the full scope of tile drain impacts in RBZ hydrology and P transport is far from clear since few studies have explicitly investigated the impacts of tile drainage designs on P loss compared to undrained conditions.

8. Future Research Considerations

Phosphorus Transport Modeling and Site Indices

Calibrated field and watershed-scale P transport models help in allocating P load estimates to different land uses and broad scale targeting of P transport mitigation practices. Incorporating variable source area hydrology algorithms into P models and agronomic PSIs show promise for improving P transport risk predictions [10,32,69,132]. However, watershed scale models are often designed to predict P transport over long time periods and over relatively large areas using historical weather and management data, potentially limiting their effectiveness as a dynamic P loss risk tool at the field scale without substantial modification. Additionally, model routines that can better capture snowmelt runoff processes and soil freeze–thaw dynamics in relation to water flow and P mobility are needed [35,59,99]. Given these potential limitations and the fact that large runoff events tend to dominate P losses from cropland to streams, developing tools that can better predict event based and real-time P fluxes and include RBZ hydro-biogeochemical impacts on P transport will be important, especially in high priority watersheds with chronic P pollution.
Combining LiDAR-based DEMs with hydrologic models and GIS tools show promise for enhancing agroecosystem services by creating opportunities to optimize agricultural land while maintaining RBZ water quality functions. For example, Shrivastav et al. [84] and Thomas et al. [71] combined LiDAR-DEMs and GIS tools to map and ground-truth Qof pathways in cropland–riparian–stream settings (Figure 4a,b). These and other hydrologic studies have clearly demonstrated the tendency for Qof heterogeneity in agricultural areas, highlighting the critical importance of targeting RBZs at known “delivery points” to intercept dissolved and entrained P in Qof prior to reaching Qsf. Kuglerová et al. [82] used a high resolution LiDAR-DEM and a hydrologic model to establish variable width forest RBZs based on soil and landscape characteristics, whereby recharge areas more vulnerable to solute leaching had wider RBZs (Figure 4c,d).
While existing watershed P transport models and PSIs will remain important tools, simplified process-based models that can readily integrate LiDAR and other digital data will be important for simulating site-specific hydrologic and P transport processes. In a review of nutrient dynamics in CC agricultural catchments, Costa et al. [99] suggested that more parsimonious P transport models that simulate major soil and hydroclimatic processes governing runoff generation and P transport may be more advantageous than larger, more complex models. Several investigators have combined process-based model outputs with Bayesian networks, machine learning, and other artificial intelligence algorithms to develop predictive hydrologic and nutrient flux models along with uncertainty estimates [133,134,135,136,137].
In addition to innovative predictive tools that can account for more of the weather driven and seasonal dynamics of P transport, longer term management practices aimed at reducing P imbalances and soil P accumulation are needed. As previously indicated, current efforts are not sufficiently attenuating P transport or eutrophication risk in the US and other countries, and that new tools and practices are needed to further curb P transport from cropland to streams. While RBZs will remain an important practice, modifications may be needed to improve soluble P removal efficiencies. Not unlike cropland, RBZs must also be managed for optimal performance if P removal is a desired ecosystem service [138,139]. To this end, more widespread and routine soil P testing of RBZs is suggested (similar to P testing for NMPs). Routinely testing RBZs for soil P status as part of agronomic NMPs could be a simple and cost-effective way to provide a baseline indicator of labile P status. Additionally, soil P data could be combined with hydrologic data to further characterize P transport potential.
Given the strong relationship between pH and P availability in soils and legacy sediments [140,141], lowering or raising pH to decrease P availability (something commonly done on cropland to increase soil P availability) in RBZ soils offers a way to further decrease DRP transport from RBZs to Qsf. However, altering soil pH has implications for plant communities, organic C cycling, and other ecological considerations. Careful research is necessary to evaluate potential tradeoffs between enhancing P sorption in RBZs via pH alterations and maintaining overall ecological integrity.
Riparian vegetation plays an important but poorly understood role in P transfer to Qsf. More research to better understand RBZ soil-vegetation interactions and their impacts on P transport is another area of need [115]. Several studies suggest the periodic harvesting of RBZ vegetation to reduce labile soil P concentrations, remove P, and presumably reduce DRP release and transport potential [86,94,97,101,115,123,138,139]. While it is clear that RBZ vegetation can affect P biogeochemistry and physical transport, it is far from clear what the optimum soil-vegetation combinations are for maximizing P attenuation. More research dedicated to soil-vegetation interactions with the goal of maximizing DRP attenuation is needed (particularly for P sensitive watersheds) to enable prescriptive management combinations to mitigate P transport. Lastly, where appropriate, a broader set of predictive approaches should be considered (i.e., Bayesian neural networks, artificial intelligence, machine learning algorithms and various hybrid models) to P loss prediction and develop real-time, dynamic P transport prediction tools that can simultaneously quantify risk and uncertainty.

Author Contributions

This article was contributed to by the authors in the following way: conceptualization, E.O.Y.; methodology, E.O.Y., D.S.R., D.P.J., P.G.V.; formal analysis, E.O.Y., D.S.R., D.P.J., P.G.V.; investigation, E.O.Y.; writing—original draft preparation, E.O.Y.; review and editing, D.S.R., D.P.J., P.G.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported in part by the U.S. Department of Agriculture, Agricultural Research Service.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable

Data Availability Statement

Data are contained within the article or cited articles in the review.

Acknowledgments

The authors would like to thank Barbara C. Storandt for her assistance with formatting references and proofreading the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wetzel, R.G. Limnology; WB Sounders and Company: Philadelphia, PA, USA, 1983. [Google Scholar]
  2. Pasek, M.A.; Sampson, J.M. Redox Chemistry in the Phosphorus Biogeochemical Cycle. Proc. Natl. Acad. Sci. USA 2014, 111, 15468. [Google Scholar] [CrossRef] [Green Version]
  3. Greaves, J.S.; Richards, A.M.S.; Bains, W.; Rimmer, P.B.; Sagawa, H.; Clements, D.L.; Seager, S.; Petkowski, J.J.; Sousa-Silva, C.; Ranjan, S.; et al. Phosphine Gas in the Cloud Decks of Venus. Nat. Astron. 2020. [Google Scholar] [CrossRef]
  4. Sims, J.T.; Pierzynski, G.M. Chemistry of Phosphorus in Soils. In Chemical Processes in Soils; Tabatabai., M.A., Sparks, D.L., Eds.; SSSA: Madison, WI, USA, 2015; pp. 151–192. [Google Scholar]
  5. Pierzynski, G.M.; McDowell, R.W.; Sims, J.T. Chemistry, Cycling, and Potential Movement of Inorganic Phosphorus in Soils. In Phosphorus: Agriculture and the Environment; Sims, J.T., Sharpley, A.N., Eds.; ASA; CSSA; SSSA: Madison, WI, USA, 2005; pp. 53–86. [Google Scholar]
  6. Smith, L.; Watzin, M.C.; Druschel, G. Relating Sediment Phosphorus Mobility to Seasonal and Diel Redox Fluctuations at the Sediment-Water Interface in a Eutrophic Freshwater Lake. Limnol. Oceanogr. 2011, 56, 2251–2264. [Google Scholar] [CrossRef]
  7. Kruse, J.; Abraham, M.; Amelung, W.; Baum, C.; Bol, R.; Kühn, O.; Lewandowski, H.; Niederberger, J.; Oelmann, Y.; Rüger, C.; et al. Innovative Methods in Soil Phosphorus Research-A Review. J. Plant Nutr. Soil Sci. 2015, 1, 43–88. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. United States Environmental Protection Agency (USEPA). National Water Quality Inventory Report; USEPA: Washington, DC, USA, 2000. Available online: http://www.epa.gov/305b/2000report/ (accessed on 8 October 2007).
  9. Carpenter, S.; Caraco, N.F.; Correll, D.L.; Horwath, R.W.; Sharpley, A.N.; Smith, V.H. Nonpoint Pollution of Surface Waters With Phosphorus and Nitrogen. Ecol. Appl. 1998, 8, 559–568. [Google Scholar] [CrossRef]
  10. Kleinman, P.J.A.; Fanelli, R.M.; Hirsch, R.M.; Buda, A.R.; Easton, Z.M.; Wainger, L.A.; Shenk, G.W. Phosphorus and the Chesapeake Bay: Lingering Issues and Emerging Concerns for Agriculture. J. Environ. Qual. 2019 48, 1191–1203. [CrossRef] [Green Version]
  11. Jarvie, H.P.; Sharpley, A.N.; Flaten, D.; Kleinman, P.J.A.; Jenkins, A.; Simmons, T. The Pivotal Role of Phosphorus in a Resilient Water–Energy–Food Security Nexus. J. Environ. Qual. 2015, 44, 1049–1062. [Google Scholar] [CrossRef]
  12. Sims, J.T.; Simard, R.R.; Joern, B.S. Phosphorus Loss in Agricultural Drainage: Historical Perspective and Current Research. J. Environ. Qual. 1998, 27, 277–293. [Google Scholar] [CrossRef] [Green Version]
  13. Young, E.O.; Briggs, R.D. Phosphorus Concentrations in Soil and Subsurface Water: A Field Study among Cropland and Riparian Buffers. J. Environ. Qual. 2008, 37, 69–78. [Google Scholar] [CrossRef]
  14. Vidon, P.; Hubbard, H.; Cuadra, P.; Hennessy, M. Storm Phosphorus Concentrations and Fluxes in Artificially Drained Landscapes of the US Midwest. Agric. Sci. 2012, 3, 474–485. [Google Scholar] [CrossRef]
  15. Gburek, W.J.; Sharpley, A.N. Hydrologic Controls on Phosphorus Loss from Upland Agricultural Watersheds. J. Environ. Qual. 1998, 27, 267–277. [Google Scholar] [CrossRef]
  16. Simard, R.R.; Beauchemin, S.; Haygarth, P.M. Potential for Preferential Pathways of Phosphorus Transport. J. Environ. Qual. 2000, 29, 97–104. [Google Scholar] [CrossRef]
  17. Bryant, R.D.; Gburek, W.J.; Veith, T.L.; Hively, W.D. Perspectives on the Potential for Hydropedology to Improve Watershed Modeling of Phosphorus Loss. Geoderma 2006, 131, 299–307. [Google Scholar] [CrossRef]
  18. Buda, A.R.; Kleinman, P.J.A.; Srinivasan, M.S.; Bryant, R.B.; Feyereisen, G.W. Effects of Hydrology and Field Management on Phosphorus Transport in Surface Runoff. J. Environ. Qual. 2009, 38, 2273–2284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Kleinman, P.J.A.; Sharpley, A.N.; Buda, A.R.; McDowell, R.W.; Allen, A.L. Soil Controls of Phosphorus in Runoff: Management Barriers and Opportunities. Can. J. Soil Sci. 2011, 91, 329–338. [Google Scholar] [CrossRef]
  20. Liu, J.; Baulch, H.M.; Macrae, M.L.; Wilson, H.F.; Elliott, J.A.; Bergström, L.; Glenn, A.J.; Vadas, P.A. Agricultural Water Quality in Cold Climates: Processes, Drivers, Management Options, and Research Needs. J. Environ. Qual. 2019, 48, 792–802. [Google Scholar] [CrossRef] [Green Version]
  21. Outram, F.N.; Cooper, R.J.; Suennenberg, G.; Hiscock, K.M.; Lovett, A.A. Antecedent Conditions, Hydrological Connectivity and Anthropogenic Inputs: Factors Affecting Nitrate and Phosphorus Transfers to Agricultural Headwater Streams. Sci. Total Environ. 2016, 545–546, 184–199. [Google Scholar] [CrossRef]
  22. Sharpley, A.N.; Kleinman, P.J.A.; Flaten, D.N.; Buda, A.R. Critical Source Area Management of Agricultural Phosphorus: Experiences, Challenges, and Opportunities. Water Sci. Technol. 2011, 64, 945–952. [Google Scholar] [CrossRef]
  23. Bol, R.; Julich, D.; Brödlin, D.; Siemens, J.; Kaiser, K.; Dippold, M.A.; Spielvogel, S.; Zilla, T.; Mewes, D.; von Blanckenburg, F.; et al. Dissolved and Colloidal Phosphorus Fluxes in Forest Ecosystems—An Almost Blind Spot in Ecosystem Research. J. Plant Nutr. Soil Sci. 2016, 179, 425–438. [Google Scholar] [CrossRef] [Green Version]
  24. Lemunyon, J.L.; Gilbert, R.G. The Concept and Need for a Phosphorus Assessment Tool. J. Prod. Agric. 1993, 6, 483–486. [Google Scholar] [CrossRef]
  25. Gebbers, R.; Adamchuk, V.I. Precision Agriculture and Food Security. Science 2010, 327, 828–831. [Google Scholar] [CrossRef]
  26. Cassman, K.G. Ecological Intensification of Cereal Production: Yield Potential, Soil Quality, and Precision Agriculture. Proc. Natl. Acad. Sci. USA 1999, 96, 5952. [Google Scholar] [CrossRef] [Green Version]
  27. Kleinman, P.J.A. Effect of Mineral and Manure Phosphorus Sources on Runoff Phosphorus. J. Environ. Qual. 2002, 31, 2026–2033. [Google Scholar] [CrossRef]
  28. Jokela, W.E.; Sherman, J.; Cavadini, J. Nutrient Runoff Losses from Liquid Dairy Manure Applied with Low-Disturbance Methods. J. Environ. Qual. 2016, 45, 1672–1679. [Google Scholar] [CrossRef] [PubMed]
  29. Hanrahan, L.R.; Jokela, W.E.; Knapp, J.R. Dairy Diet Phosphorus and Rainfall Timing Effects on Runoff Phosphorus from Land-Applied Manure. J. Environ. Qual. 2009, 38, 212–217. [Google Scholar] [CrossRef] [Green Version]
  30. Hill, J.E.; Cade-Menun, B.J. Phosphorus-31 Nuclear Magnetic Resonance Spectroscopy Transect Study of Poultry Operations on the Delmarva Peninsula. J. Environ. Qual. 2009, 37, 1–9. [Google Scholar] [CrossRef] [PubMed]
  31. Stout, L.M.; Nguyen, T.; Jaisi, D.P. Relationship of Phytate, Phytate Mineralizing Bacteria, and Beta-Propeller Genes along a Coastal Tributary to the Chesapeake Bay. Soil Sci. Soc. Am. J. 2016, 80, 84–96. [Google Scholar] [CrossRef]
  32. Collick, A.S.; Veith, T.L.; Fuka, D.R.; Kleinman, P.J.A.; Buda, A.R.; Weld, J.L.; Bryant, R.B.; Vadas, P.A.; White, M.J.; Harmel, R.D.; et al. Improved Simulation of Edaphic and Manure Phosphorus Loss in SWAT. J. Environ. Qual. 2014, 45, 1215–1225. [Google Scholar] [CrossRef] [PubMed]
  33. Good, L.W.; Vadas, P.; Panuska, J.C.; Bonilla, C.A.; Jokela, W.E. Testing the Wisconsin P Index with Year-Round, Field-Scale Runoff Monitoring. J. Environ. Qual. 2012, 41, 1730–1740. [Google Scholar] [CrossRef] [Green Version]
  34. Good, L.W.; Carvin, R.; Lamba, J.; Fitzpatrick, F.A. Seasonal Variation in Sediment and Phosphorus Yields in Four Wisconsin Agricultural Watersheds. J. Environ. Qual. 2019, 48, 950–958. [Google Scholar] [CrossRef]
  35. Hoffman, A.R.; Polebitski, A.S.; Penn, M.R.; Busch, D.L. Long-Term Variation in Agricultural Edge-of-Field Phosphorus Transport During Snowmelt, Rain, and Mixed Runoff events. J. Environ. Qual. 2019, 48, 931–940. [Google Scholar] [CrossRef] [PubMed]
  36. King, K.W.; Williams, M.R.; Macrae, M.L.; Fausey, N.R.; Frankenberger, J.; Smith, D.R.; Kleinman, P.J.A.; Brown, L.C. Phosphorus Transport in Agricultural. Subsurface Drainage: A Review. J. Environ. Qual. 2015, 44, 467–485. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Dunne, E.J.; Reddy, K.R.; Clark, M.W. Biogeochemical Indices of Phosphorus Retention and Release by Wetland Soils and Adjacent Stream Sediments. Wetlands 2006, 26, 1026–1041. [Google Scholar] [CrossRef]
  38. Kronvang, B.; Bechman, M.; Lundekvam, H.; Behrendt, H.; Rubæk, G.H.; Schoumans, O.F.; Syversen, N.; Andersen, H.E.; Hoffmann, C.C. Phosphorus Losses From Agricultural Areas in River Basins: Effects and Uncertainties of Targeted Mitigation Measures. J. Environ. Qual. 2005, 34, 2129–2144. [Google Scholar] [CrossRef] [PubMed]
  39. Withers, P.J.A.; Haygarth, P.M. Agriculture, Phosphorus and Eutrophication: A European Perspective. Soil Use Manage 2007, 23, 1–4. [Google Scholar] [CrossRef]
  40. Jarvie, H.P.; Sharpley, A.N.; Spears, B.; Buda, A.R.; May, L.; Kleinman, P.J.A. Water Quality Remediation Faces Unprecedented Challenges from Legacy Phosphorus. Environ. Sci. Technol. 2013, 47, 8997–8998. [Google Scholar] [CrossRef] [Green Version]
  41. Michaud, A.R.; Poirier, S.C.; Whalen, J.K. Tile Drainage as a Hydrologic Pathway for Phosphorus Export From an Agricultural Subwatershed. J. Environ. Qual. 2018, 48, 64–72. [Google Scholar] [CrossRef]
  42. Mingus, K.A.; Liang, X.; Massoudieh, A.; Jaisi, D.P. Stable Isotopes and Bayesian Modeling Methods of Tracking Sources and Differentiating Bioavailable and Recalcitrant Phosphorus Pools in Suspended Particulate Matter. Environ. Sci. Technol. 2018, 53, 69–76. [Google Scholar] [CrossRef]
  43. Li, Q.; Yuan, H.; Li, H.; Wang, D.; Jin, Y.; Jaisi, D.P. Loading and Bioavailability of Colloidal Phosphorus in the Estuarine Gradient of the Deer Creek-Susquehanna River Transect in the Chesapeake Bay. J. Geophys. Res. Biogeosci. 2019, 124, 3717–3726. [Google Scholar] [CrossRef]
  44. Stackpoole, S.M.; Stets, E.G.; & Sprague, L.A. Variable Impacts of Contemporary Versus Legacy Agricultural Phosphorus on US River Water Quality. Proc. Natl. Acad. Sci. USA 2019, 116, 20562–20567. [Google Scholar] [CrossRef] [Green Version]
  45. Klaiber, L.B.; Kramer, S.R.; Young, E.O. Impacts of Tile Drainage on Phosphorus Losses from Edge-of-Field Plots in the Lake Champlain Basin of New York. Water 2020, 12, 328. [Google Scholar] [CrossRef] [Green Version]
  46. Su, J.J.; van Bochove, E.; Thériault, G.; Novotna, B.; Khaldoune, J.; Denault, J.T.; Zhou, J.; Nolin, M.C.; Hu, C.X.; Bernier, M.; et al. Effects of Snowmelt on Phosphorus and Sediment Losses from Agricultural Watersheds in Eastern Canada. Agric. Water Manag. 2011, 98, 867–876. [Google Scholar] [CrossRef]
  47. Danz, M.E.; Corsi, S.R.; Brooks, W.R.; Bannerman, R.T. Characterizing Response of Total Suspended Solids and Total Phosphorus Loading to Weather and Watershed Characteristics for Rainfall and Snowmelt Events in Agricultural Watersheds. J. Hydrol. 2013, 507, 249–261. [Google Scholar] [CrossRef]
  48. Jaisi, D.P.; Mingus, K.A.; Joshi, S.R.; Upreti, K.; Sun, M.; McGrath, J. Massudieh Linking Sources, Transformation, and Loss of Phosphorus in the Soil-Water Continuum in a Coastal Environment. In Multi-Scale Biogeochemical Processes in Soil Ecosystems: Critical Reactions and Resilience to Climate Changes; Yang, Y., Keiluweit, M., Senesi, N., Xing, B., Eds.; Wiley: Hoboken, NJ, USA, 2021. [Google Scholar]
  49. Upreti, K.; Joshi, S.R.; McGrath, J.; Jaisi, D.P. Factors Controlling Phosphorus Mobilization in a Coastal Plain Tributary to the Chesapeake Bay. Soil Sci. Soc. Am. J. 2015, 79, 815–825. [Google Scholar] [CrossRef] [Green Version]
  50. Grundtner, A.; Gupta, S.; Bloom, P. River Bank Materials as a Source and as Carriers of Phosphorus to Lake Pepin. J. Environ. Qual. 2014, 43, 1991–2001. [Google Scholar] [CrossRef]
  51. Ishee, E.R.; Ross, D.S.; Garvey, K.M.; Bourgault, R.R.; Ford, C.R. Phosphorus Characterization and Contribution From Eroding Streambank Soils of Vermont’s Lake Champlain Basin. J. Environ. Qual. 2015, 44, 1745–1753. [Google Scholar] [CrossRef] [Green Version]
  52. Inamdar, S.; Johnson, E.; Rowland, R.; Warner, D.; Walter, R.; Merritts, D. Freeze-Thaw Processes and Intense Rainfall: The One-Two Punch for High Sediment and Nutrient Loads from Mid-Atlantic Watersheds. Biogeochemistry 2018, 141, 333–349. [Google Scholar] [CrossRef] [Green Version]
  53. Ross, D.S.; Wemple, B.C.; Willson, L.J.; Balling, C.M.; Underwood, K.L.; Hamshaw, S.D. Impact of an Extreme Storm Event on River Corridor Bank Erosion and Phosphorus Mobilization in a Mountainous Watershed in the Northeastern United States. JGR Biogeosci. 2019, 124, 18–32. [Google Scholar]
  54. Vadas, P.A.; Good, L.W.; Jokela, W.E.; Karthikeyan, K.G.; Arriaga, F.J.; Stock, M. Quantifying the Impact of Seasonal and Short-Term Manure Application Decisions on Phosphorus Loss in Surface Runoff. J. Environ. Qual. 2017, 46, 1395–1402. [Google Scholar] [CrossRef] [Green Version]
  55. Bilotta, G.S.; Brazier, R.E.; Haygarth, P.M. The Impacts of Grazing Animals on the Quality of Soils, Vegetation, and Surface Waters in Intensively Managed Grasslands. Adv. Agron. 2007, 94, 237–280. [Google Scholar]
  56. Vadas, P.A.; Busch, D.L.; Powell, J.M.; Brink, G.E. Monitoring Runoff from Cattle-Grazed Pastures for a Phosphorus Loss Quantification Tool. Agric. Ecosyst. Environ. 2015, 199, 124–131. [Google Scholar] [CrossRef] [Green Version]
  57. Hansen, N.C.; Gupta, S.C.; Moncrief, J.F. Snowmelt Runoff, Sediment, and Phosphorus Losses under Three Different Tillage Systems. Soil Tillage Res. 2000, 57, 93–100. [Google Scholar] [CrossRef]
  58. Stock, M.N.; Arriaga, F.J.; Vadas, P.A.; Good, L.W.; Casler, M.D.; Karthikeyan, K.G.; Zopp, Z. Fall Tillage Reduced Nutrient Loads from Liquid Manure Application During the Freezing Season. J. Environ. Qual. 2019, 48, 889–898. [Google Scholar] [CrossRef] [Green Version]
  59. Vadas, P.A.; Stock, M.N.; Arriaga, F.J.; Good, L.W.; Karthikeyan, K.G.; Zopp, Z.P. Dynamics of Measured and Simulated Dissolved Phosphorus in Runoff from Winter-Applied Dairy Manure. J. Environ. Qual. 2019, 48, 899–906. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Zopp, Z.P.; Ruark, M.D.; Thompson, A.M.; Stuntebeck, T.D.; Cooley, E.; Radatz, A.; Radatz, T. Effects of Manure and Tillage on Edge-of-Field Phosphorus Loss in Seasonally Frozen Landscapes. J. Environ. Qual. 2019, 48, 966–977. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Vadas, P.A.; Kleinman, P.J.A.; Sharpley, A.N.; Turner, B.L. Relating Soil Phosphorus to Dissolved Phosphorus in Runoff: A Single Extraction Coefficient for Water Quality Modeling. J. Environ. Qual. 2005, 34, 572–580. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Wilson, H.; Elliott, J.; Macrae, M.; Glenn, A. Near-Surface Soils as a Source of Phosphorus in Snowmelt Runoff from Cropland. J. Environ. Qual. 2019, 48, 921–930. [Google Scholar] [CrossRef] [Green Version]
  63. Osterholz, W.; King, K.; Williams, M.; Hanrahan, B.; Duncan, E. Stratified Soil Sampling Improves Predictions of P Concentration in Surface Runoff and Tile Discharge. Soil Syst. 2020, 4, 67. [Google Scholar] [CrossRef]
  64. Vidon, P.; Allan, C.; Burns, D.; Duval, T.P.; Gurwick, N.; Inamdar, S.; Lowrance, R.; Okay, J.; Scott, D.; Sebestyen, S. Hot Spots and Hot Moments in Riparian Zones: Potential for Improved Water Quality Management. J. Am. Water Resour. Assoc. 2010, 46, 278–298. [Google Scholar] [CrossRef]
  65. Beven, K.J.; Kirkby, M.J. A Physically-Based Variable Contributing Area Model of Basin Hydrology. Hydrol. Sci. Bull. 1979, 24, 43–69. [Google Scholar] [CrossRef] [Green Version]
  66. Gburek, W.J.; Drungil, C.C.; Srinivasan, M.S.; Needelman, B.A.; Woodward, D.E. Variable-Source-Area Controls on Phosphorus Transport: Bridging the Gap between Research and Design. J. Soil Water Conserv. 2020, 57, 534–543. [Google Scholar]
  67. Walter, M.T.; Steenhuis, T.S.; Mehta, V.K.; Thongs, D.; Zion, M.; Schneiderman, E. Refined Conceptualization of TOPMODEL for Shallow Subsurface Flows. Hydrol. Process. 2002, 16, 2014–2046. [Google Scholar] [CrossRef]
  68. Walter, M.T.; Walter, M.F.; Brooks, E.S.; Steenhuis, T.S.; Boll, J.; Weiler, K.R. Hydrologically Sensitive Areas: Variable Source Area Hydrology Implications for Water Quality Risk Assessment. J. Soil Water Conserv. 2000, 55, 277–284. [Google Scholar]
  69. Easton, Z.M.; Fuka, D.R.; Walter, M.T.; Cowan, D.M.; Schneiderman, E.M.; Steenhuis, T.S. Re-conceptualizing the Soil and Water Assessment Tool (SWAT) Model to Predict Runoff from Variable Source Areas. J. Hydrol. 2008, 348, 279–291. [Google Scholar] [CrossRef]
  70. Agnew, L.J.; Lyon, S.; Gérard-Marchant, P.; Collins, V.B.; Lembo, A.J.; Steenhuis, T.S.; Walter, M.T. Identifying Hydrologically Sensitive Areas: Bridging Science and Application. J. Environ. Mgt. 2006, 78, 64–76. [Google Scholar]
  71. Thomas, I.A.; Jordan, P.; Mellander, P.E.; Fenton, O.; Shine, O.; ÓhUallacháin, D.; Creamer, R.; McDonald, N.T.; Dunlop, P.; Murphy, P.N.C. Improving the Identification of Hydrologically Sensitive Areas Using LiDAR DEMs for the Delineation and Mitigation of Critical Source Areas of Diffuse Pollution. Sci. Total Environ. 2016, 556, 276–290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Tilman, D.; Balzer, C.; Hill, J.; Befort, B.L. Global Food Demand and the Sustainable Intensification of Agriculture. Proc. Natl. Acad. Sci. USA 2011, 108, 20260–20264. [Google Scholar] [CrossRef] [Green Version]
  73. Tomer, M.D.; Porter, S.A.; James, D.E.; Boomer, K.M.B.; Kostel, J.A.; McLellan, E. Combining Precision Conservation Technologies into a Flexible Framework to Facilitate Agricultural Watershed Planning. J. Soil Water Conserv. 2013, 68, 113A–120A. [Google Scholar] [CrossRef] [Green Version]
  74. Young, E.O. Soil Nutrient Management: Fueling Agroecosystem Sustainability. Int. J. Agr. Sustain. 2020, 18, 444–448. [Google Scholar] [CrossRef]
  75. Nelson, N.O.; Parsons, J.E. Basic Approaches to Modeling Phosphorus Leaching. In Modeling Phosphorus in the Environment; Radcliffe, D.E., Cabrera, M.L., Eds.; CRC Press: Boca Raton, FL, USA, 2007; pp. 81–103. [Google Scholar]
  76. Lowrance, R.; Altier, L.S.; Williams, R.G.; Inamdar, S.P.; Sheridan, J.M.; Bosch, D.D.; Hubbard, R.K.; Thomas, D.L. REMM: The Riparian Ecosystem Management Model. J. Soil Water Conserv. 2000, 55, 27–34. [Google Scholar]
  77. Wang, Z.; Zhang, T.Q.; Tan, C.S.; Wang, X.; Taylor, R.A.J.; Qi, Z.M.; Yang, J.W. Modeling the Impacts of Manure on Phosphorus Loss in Surface Runoff and Subsurface Drainage. J. Environ. Qual. 2019, 48, 39–46. [Google Scholar] [CrossRef] [Green Version]
  78. Vidon, P.G.; Welsh, M.K.; Hassanzadeh, Y.T. Twenty Years of Riparian Zone Research (1997–2017): Where to Next? J. Environ. Qual. 2019, 48, 248–260. [Google Scholar] [CrossRef] [PubMed]
  79. Hassanzadeh, Y.T.; Vidon, P.G.; Gold, A.J.; Pradhanang, S.M.; Addy Lowder, K. RZ-TRADEOFF: A New Model to Estimate Riparian Water and Air Quality Functions. Water 2019, 11, 769. [Google Scholar] [CrossRef] [Green Version]
  80. Zhu, A.X.; Hudson, B.; Burt, J.; Lubich, K.; Simonson, D. Soil Mapping Using GIS, Expert Knowledge, and Fuzzy Logic. Soil Sci. Soc. Amer. J. 2001, 65, 1463–1472. [Google Scholar] [CrossRef] [Green Version]
  81. McBratney, A.B.; Mendonca Santos, M.L.; Minasny, B. On Digital Soil Mapping. Geoderma 2003, 117, 3–52. [Google Scholar] [CrossRef]
  82. Kuglerová, L.; Agren, A.; Jansson, R.; Laudon, H. Towards Optimizing Riparian Buffer Zones: Ecological and Biogeochemical Implications for Forest Management. For. Ecol. Manag. 2014, 334, 74–84. [Google Scholar]
  83. Wallace, C.W.; McCarty, G.; Lee, S.; Brooks, R.P.; Veith, T.L.; Kleinman, P.J.A.; Sadeghi, A.M. Evaluating Concentrated Flowpaths in Riparian Forest Buffer Contributing Areas Using LiDAR Imagery and Topographic Metrics. Remote Sens. 2018, 10, 614. [Google Scholar] [CrossRef]
  84. Shrivastav, M.; Mickelson, S.K.; Webber, D. Using ArcGIS Hydrologic Modeling and LiDAR Digital Elevation Data to Evaluate Surface Runoff Interception Performance of Riparian Vegetative Filter Strip Buffers in Central Iowa. J. Soil Water Conserv. 2020, 75, 123–129. [Google Scholar] [CrossRef] [Green Version]
  85. Webber, D.F.; Bansal, M.; Mickelson, S.K.; Helmers, M.J.; Arora, K.; Gelder, B.K.; Shrivastav, M.; Judge, C.J. Assessing Surface Flowpath Interception by Vegetative Buffers Using ArcGIS Hydrologic Modeling and Geospatial Analysis for Rock Creek Watershed, Central Iowa. Trans. Am. Soc. Agric. Biol. Eng. 2018, 61, 273–283. [Google Scholar] [CrossRef] [Green Version]
  86. Hoffman, C.C.; Kjaergaard, C.; Uusi-Kämppä, J.; Bruun Hansen, H.C.; Kronvang, B. Phosphorus Retention in Riparian Buffers: Review of Their Efficiency. J. Environ. Qual. 2009, 38, 1942–1955. [Google Scholar] [CrossRef]
  87. Lyons, J.B.; Görres, J.H.; Amador, J.A. Spatial and Temporal Variability of Phosphorus Retention in a Riparian Forest Soil. J. Environ. Qual. 1998, 27, 895–903. [Google Scholar] [CrossRef]
  88. Young, E.O.; Ross, D.S. Total and Labile Phosphorus Concentrations as Influenced by Riparian Buffer Soil Properties. J. Environ. Qual. 2016, 45, 294–304. [Google Scholar] [CrossRef]
  89. Perillo, V.; Ross, D.; Wemple, B.; Balling, C.; Lemieux, L. Stream Corridor Soil Phosphorus Availability in a Forested-Agricultural Mixed Land Use Watershed. J. Environ. Qual. 2019, 48, 185–192. [Google Scholar] [CrossRef] [Green Version]
  90. Young, E.O.; Ross, D.S.; Alves, C.; Villars, T. Soil and Landscape Influences on Native Riparian Phosphorus Availability in Three Lake Champlain Basin Stream Corridors. J. Soil Water Conserv. 2012, 67, 1–7. [Google Scholar] [CrossRef]
  91. Rosenberg, B.D.; Schroth, A.W. Coupling of Reactive Riverine Phosphorus and Iron Species during Hot Transport Moments: Impacts of Land Cover and Seasonality. Biogeochemistry 2017, 132, 103–122. [Google Scholar] [CrossRef]
  92. Dosskey, M.G. Toward Quantifying Water Pollution Abatement in Response to Installing Buffers on Cropland. Environ. Manag. 2001, 28, 577–598. [Google Scholar] [CrossRef]
  93. Wang, L. Effects of Watershed Best Management Practices on Habitat and Fish in Wisconsin Streams. J. Am. Water Resour. Assoc. 2002, 38, 663–680. [Google Scholar] [CrossRef]
  94. Kieta, K.A.; Owens, P.N.; Lobb, D.A.; Vanrobaeys, J.A.; Flaten, D.N. Phosphorus Dynamics in Vegetated Buffer Strips in Cold Climates: A Review. Environ. Reviews 2018, 26, 255–272. [Google Scholar] [CrossRef]
  95. Carlyle, G.C.; Hill, A.R. Groundwater Phosphate Dynamics in a River Riparian Zone: Effects of Hydrologic Flowpaths, Lithology and Redox Chemistry. J. Hydrol. 2001, 247, 151–168. [Google Scholar] [CrossRef]
  96. Dupas, R.; Gruau, G.; Gu, S.; Humbert, G.; Jaffrézic, A.; Gascuel-Odoux, C. Groundwater Control of Biogeochemical Processes Causing Phosphorus Release from Riparian Wetlands. Water Res. 2015, 84, 307–314. [Google Scholar] [CrossRef]
  97. Stutter, M.I.; Langan, S.J.; Lumsdon, D.G. Vegetated Buffer Strips Can Lead to Increased Release of Phosphorus to Waters: A Biogeochemical Assessment of the Mechanisms. Environ. Sci. Technol. 2009, 43, 1858–1863. [Google Scholar] [CrossRef]
  98. Liu, J.; Macrae, M.L.; Elliott, J.A.; Baulch, H.M.; Wilson, H.F.; Kleinman, P.J.A. Impacts of Cover Crops and Crop Residues on Phosphorus Losses in Cold Climates: A Review. J. Environ. Qual. 2019, 48, 850–868. [Google Scholar] [CrossRef] [Green Version]
  99. Costa, D.; Baulch, H.; Elliott, J.; Pomeroy, J.; Wheater, H. Modelling Nutrient Dynamics in Cold Agricultural Catchments: A Review. Environ. Modell. Softw. 2020, 124, 104586. [Google Scholar] [CrossRef]
  100. Young, E.O.; Ross, D.S.; Jaynes, D.B. Editorial: Riparian Buffer Nutrient Dynamics and Water Quality. Front. Environ. Sci. 2019, 7, 76. [Google Scholar] [CrossRef]
  101. Stutter, M.; Kronvang, B.; ÓhUallacháin, D.; Rozemeijer, J. Current Insights into the Effectiveness of Riparian Management, Attainment of Multiple Benefits, and Potential Technical Enhancements. J. Environ. Qual. 2019, 48, 236–247. [Google Scholar] [CrossRef] [Green Version]
  102. Cole, L.J.; Stockan, J.; Helliwell, R. Managing Riparian Buffer Strips to Optimise Ecosystem Services: A Review. Agric. Ecosyst. Environ. 2020, 296, 106891. [Google Scholar] [CrossRef]
  103. Condron, L.M.; Turner, B.L.; Cade-Menun, B.J. Chemistry and Dynamics of Soil Organic Phosphorus. In Phosphorus: Agriculture and the Environment; Sims, J.T., Sharpley, A.N., Eds.; ASA; CSSA; SSSA: Madison, WI, USA, 2005; pp. 87–121. [Google Scholar]
  104. Young, E.O.; Ross, D.S.; Cade-Menun, B.J.; Lu, C.W. Phosphorus Speciation in Riparian Soils: A Phosphorus-31 Nuclear Magnetic Resonance Spectroscopy and Enzyme Hydrolysis Study. Soil Sci. Soc. Am. J. 2013, 77, 1636–1647. [Google Scholar] [CrossRef]
  105. Griffith, K.E.; Young, E.O.; Klaiber, L.B.; Kramer, S.R. Winter Rye Cover Crop Impacts on Runoff Water Quality in a Northern New York (USA) Tile-Drained Maize Agroecosystem. Water Air Soil Pollut. 2020, 231, 1–16. [Google Scholar] [CrossRef]
  106. Smeck, N.E. Phosphorus Dynamics in Soils and Landscapes. Geoderma 1985, 36, 185–199. [Google Scholar] [CrossRef]
  107. Walker, T.W.; Syers, J.K. The Fate of Phosphorus during Pedogenesis. Geoderma 1976, 15, 1–19. [Google Scholar] [CrossRef]
  108. Yanai, R.D. Phosphorus Budget of a 70-Year-Old Northern Hardwood Forest. Biogeochemistry 1992, 17, 1–22. [Google Scholar] [CrossRef]
  109. Yanai, R.D. The Effect of Whole-Tree Harvest on Phosphorus Cycling in a Northern Hardwood Forest. For. Ecol. Manag. 1998, 104, 281–295. [Google Scholar] [CrossRef]
  110. Laboski, C.A.M.; Lamb, J.A. Changes in Soil Test Phosphorus Concentration after Application of Manure or Fertilizer. Soil Sci. Soc. Am. J. 2003, 67, 544–554. [Google Scholar] [CrossRef]
  111. Young, E.O.; Ross, D.S. Phosphorus Mobilization in Flooded Riparian Soils from the Lake Champlain Basin, VT, USA. Front. Environ. Sci. 2018, 6, 120. [Google Scholar] [CrossRef] [Green Version]
  112. Zaimes, G.N.; Schultz, R.C.; Isenhart, T.M. Streambank Soil and Phosphorus Losses under Different Riparian Land-Uses in Iowa. J. Am. Water Resour. Assoc. 2008, 44, 935–947. [Google Scholar] [CrossRef]
  113. Sekely, A.C.; Mulla, D.J.; Bauer, D.W. Streambank Slumping and Its Contribution to the Phosphorus and Suspended Sediment Loads to the Blue Earth River, Minnesota. J. Soil Water Cons. 2002, 57, 243–250. [Google Scholar]
  114. Gupta, S.C.; Kessler, A.C.; Brown, M.K.; Zvomuya, F. Climate and Agricultural Land Use Change Impacts on Streamflow in the Upper Midwestern United States. J. Am. Water Resour. Assoc. 2015, 51, 5301–5317. [Google Scholar] [CrossRef]
  115. Dosskey, M.G.; Vidon, P.; Gurwick, N.P.; Allan, C.J.; Duval, T.P.; Lowrance, R. The Role of Riparian Vegetation in Protecting and Improving Chemical Water Quality in Streams. J. Am. Water Resour. Assoc. 2010, 46, 261–277. [Google Scholar] [CrossRef]
  116. Inamdar, S.; Sienkiewicz, N.; Lutgen, A.; Jiang, G.; Kan, J. Streambank Legacy Sediments in Surface Waters: Phosphorus Sources or Sinks? Soil Syst. 2020, 4, 30. [Google Scholar] [CrossRef]
  117. Chardon, W.J.; Schoumans, O.F. Solubilization of Phosphorus: Concepts and Process Description of Chemical Mechanisms. In Phosphorus Losses from Agricultural Soils: Processes at the Field-Scale; Chardon, W.J., Schoumans, O.F., Eds.; Cost Action 832: Quantifying the Agricultural Contribution to Eutrophication; ALTERRA: Wageningen, The Netherlands, 2002; pp. 44–52. [Google Scholar]
  118. McDowell, R.W.; Biggs, B.J.F.; Sharpley, A.N.; Nguyen, L. Connecting Phosphorus Loss from Agricultural Landscapes to Surface Water Quality. Chem. Ecol. 2004, 20, 1–40. [Google Scholar] [CrossRef]
  119. Jordan, T.E.; Correll, D.L.; Weller, D. Nutrient Interception by a Riparian Forest Receiving Inputs from Adjacent Cropland. J. Environ. Qual. 1993, 22, 467–473. [Google Scholar] [CrossRef] [Green Version]
  120. Osborne, L.L.; Kovacic, D.A. Riparian Vegetated Buffer Strips in Water Quality Restoration and Stream Management. Freshwater Biol. 1993, 29, 243–258. [Google Scholar] [CrossRef]
  121. Clausen, J.C.; Guillard, K.; Sigmund, C.M.; Dors, K.M. Water Quality Changes from Riparian Buffer Restoration in Connecticut. J. Environ. Qual. 2000, 29, 1751–1761. [Google Scholar] [CrossRef] [Green Version]
  122. Uusi-Kamppa, J.; Turtola, E.; Hartikainen, H.; Ylaranta, T. The Interactions of Buffer Zones and Phosphorus Runoff. In Buffer Zones: Their Processes and Potential in Water Protection; Haycock, N.E., Ed.; Quest Environmental: Hertfordshire, UK, 2001; pp. 43–53. [Google Scholar]
  123. Roberts, W.M.; Stutter, M.I.; Haygarth, P.M. Phosphorus Retention and Remobilization in Vegetated Buffer Strips: A Review. J. Environ. Qual. 2012, 41, 389–399. [Google Scholar] [CrossRef]
  124. Spruill, T.B. Statistical Evaluation of Effects of Riparian Buffers on Nitrate and Ground Water Quality. J. Environ. Qual. 2000, 29, 1523–1538. [Google Scholar] [CrossRef]
  125. Young, E.O.; Briggs, R.D. Nitrogen Dynamics Among Cropland and Riparian Buffers: Soil-Landscape Influences. J. Environ. Qual. 2007, 36, 801–814. [Google Scholar] [CrossRef]
  126. Gu, S.; Gruau, G.; Dupas, R.; Rumpel, C.; Crème, A.; Fovet, O.; Gascuel-Odoux, C.; Jeanneau, L.; Humbert, G.; Petitjean, P. Release of Dissolved Phosphorus from Riparian Wetlands: Evidence for Complex Interactions among Hydroclimate Variability, Topography and Soil Properties. Sci. Total Environ. 2017, 598, 421–431. [Google Scholar] [CrossRef]
  127. Kumaragamage, D.; Amarawansha, E.A.G.S.; Indraratne, S.P.; Jayarathne, P.D.K.D.; Flaten, D.N.; Zvomuya, F.; Akinremi, O.O. Degree of Phosphorus Saturation as a Predictor of Redox-Induced Phosphorus Release from Flooded Soils to Floodwater. J. Environ. Qual. 2019, 48, 1817–1825. [Google Scholar] [CrossRef]
  128. Hens, M.; Merckx, R. Functional Characterization of Colloidal Phosphorus Species in the Soil Solution of Sandy Soils. Environ. Sci. Technol. 2001, 35, 493–500. [Google Scholar] [CrossRef]
  129. Weaver, M.M. History of Tile Drainage; Weaver: Waterloo, NY, USA; Valley Offset, Inc.: Deposit, NY, USA, 1964. [Google Scholar]
  130. Young, E.O.; Geibel, J.G.; Ross, D.S. Influence of Controlled Drainage and Liquid Dairy Manure Application on Phosphorus Leaching from Intact Soil Cores. J. Environ. Qual. 2017, 46, 80–87. [Google Scholar] [CrossRef] [PubMed]
  131. Scalenghe, R.; Edwards, A.C.; Marsan, F.A.; Barberis, E. The Effect of Reducing Conditions on the Solubility of Phosphorus in a Diverse Range of European Agricultural Soils. Eur. J. Soil Sci. 2002, 53, 439–447. [Google Scholar] [CrossRef]
  132. Marjerison, R.D.; Dahlke, H.; Easton, Z.M.; Seifert, S.; Walter, M.T. A Phosphorus Index Transport Factor Based on Variable Source Area Hydrology for New York State. J. Soil Water Conserv. 2011, 66, 149–157. [Google Scholar] [CrossRef] [Green Version]
  133. Sperotto, A.; Molina, J.L.; Torresan, S.; Critto, A.; Pulido-Velazquez, M.; Marcomini, A. A Bayesian Networks Approach for the Assessment of Climate Change Impacts on Nutrient Loading. Environ. Sci. Policy 2019, 100, 21–36. [Google Scholar] [CrossRef]
  134. Chen, S.H.; Jakeman, A.J.; Norton, J.P. Artificial Intelligence Techniques: An Introduction to Their Use for Modelling Environmental Systems. Math. Comput. Simul. 2008, 78, 379–400. [Google Scholar] [CrossRef]
  135. Ahmed, A.N.; Othman, F.B.; Afan, H.A.; Elsha, A. Machine Learning Methods for Better Water Quality Prediction. J. Hydrol. 2019, 578. [Google Scholar] [CrossRef]
  136. Choubin, B.; Darabi, H.; Rahmati, O.; Sajedi-Hosseini, F.; Kløve, B. River Suspended Sediment Modelling Using the CART Model: A Comparative Study of Machine Learning Techniques. Sci. Total Environ. 2018, 615, 272–281. [Google Scholar] [CrossRef]
  137. Chebud, Y.; Naja, G.M.; Rivero, R.G. Water Quality Monitoring Using Remote Sensing and an Artificial Neural Network. Water Air Soil Pollut. 2012, 223, 4875–4887. [Google Scholar] [CrossRef]
  138. Habibiandehkordi, R.; Lobb, D.A.; Owens, P.N.; Flaten, D.N. Effectiveness of Vegetated Buffer Strips in Controlling Legacy Phosphorus Exports from Agricultural Land. J. Environ. Qual. 2019, 48, 314–321. [Google Scholar] [CrossRef] [Green Version]
  139. Hille, S.; Graeber, D.; Kronvang, B.; Rubæk, G.H.; Onnen, N.; Molina-Navarro, E.; Baattrup-Pedersen, A.; Heckrath, G.J.; Stutter, M.I. Management Options to Reduce Phosphorus Leaching from Vegetated Buffer Strips. J. Environ. Qual. 2018, 48, 322–329. [Google Scholar] [CrossRef] [Green Version]
  140. Penn, C.; Camberato, J. A Critical Review on Soil Chemical Processes That Control How Soil pH Affects Phosphorus Availability to Plants. Agriculture 2019, 9, 120. [Google Scholar] [CrossRef] [Green Version]
  141. Doydora, S.; Gatiboni, L.; Grieger, K.; Hesterberg, D.; Jones, J.L.; McLamore, E.S.; Peters, R.; Sozzani, R.; Van den Broeck, L.; Duckworth, O.W. Accessing Legacy Phosphorus in Soils. Soil Syst. 2020, 4, 74. [Google Scholar] [CrossRef]
Figure 1. US livestock farms subject to federal Clean Water Act regulations or receiving grant monies must implement cropland nutrient management plans (NMPs) to reduce nonpoint source pollutant loss to open waters. Agronomic P site indices (PSIs) capture soil and management factors affecting annual P loss potential in overland flows and are used to rank P loss potential by fields.
Figure 1. US livestock farms subject to federal Clean Water Act regulations or receiving grant monies must implement cropland nutrient management plans (NMPs) to reduce nonpoint source pollutant loss to open waters. Agronomic P site indices (PSIs) capture soil and management factors affecting annual P loss potential in overland flows and are used to rank P loss potential by fields.
Soilsystems 05 00015 g001
Figure 2. Hydrologic pathways contributing to streamflow along the cropland–riparian–stream continuum.
Figure 2. Hydrologic pathways contributing to streamflow along the cropland–riparian–stream continuum.
Soilsystems 05 00015 g002
Figure 3. Conceptual diagram depicting hydro-biogeochemical and management factors driving phosphorus (P) fate and transport in cold climates (CCs). Dotted lines represent hydrologic flow pathways that transport P and other solutes. Red arrows represent P inputs into the system or P release via desorption reactions. Green arrows represent P removal via sorption reactions or metabolic uptake of dissolved inorganic P from solution. White arrows indicate biogeochemical processes affecting P bioavailability including pH fluctuations, redox reactions, organic matter cycling (mineralization), and hydrolysis of organic P that affect net P release and fluxes. Note presence of tile drains, stream bank erosion, and other aspects discussed in the text are omitted due to space limitations.
Figure 3. Conceptual diagram depicting hydro-biogeochemical and management factors driving phosphorus (P) fate and transport in cold climates (CCs). Dotted lines represent hydrologic flow pathways that transport P and other solutes. Red arrows represent P inputs into the system or P release via desorption reactions. Green arrows represent P removal via sorption reactions or metabolic uptake of dissolved inorganic P from solution. White arrows indicate biogeochemical processes affecting P bioavailability including pH fluctuations, redox reactions, organic matter cycling (mineralization), and hydrolysis of organic P that affect net P release and fluxes. Note presence of tile drains, stream bank erosion, and other aspects discussed in the text are omitted due to space limitations.
Soilsystems 05 00015 g003
Figure 4. Model estimates of overland runoff flow (Qof) pathways using light detection and ranging (LiDAR) based digital elevation models from Shrivastav et al. [84] (a) and Thomas et al. [71] (b) illustrating the tendency for non-uniform Qof, and highlights the critical importance of targeting riparian buffers at known Oof delivery points to intercept sediment and phosphorus prior to reaching streams. Yellow and red in 4b indicate Qof areas and blue circles indicate Qof delivery points. Variable width riparian forest buffer zones predicted by a LiDAR based groundwater hydrology model by Kuglerová et al. [82] (c,d). Panel 4c shows a sunlit LiDAR image of a stream section; blue lines are small streams and red stars are runoff collection points. In panel 4d, blue layers indicate model predicted groundwater discharge zones (darker blues indicate greater fluxes) and red areas are intermittent streams. All figures reproduced with permission.
Figure 4. Model estimates of overland runoff flow (Qof) pathways using light detection and ranging (LiDAR) based digital elevation models from Shrivastav et al. [84] (a) and Thomas et al. [71] (b) illustrating the tendency for non-uniform Qof, and highlights the critical importance of targeting riparian buffers at known Oof delivery points to intercept sediment and phosphorus prior to reaching streams. Yellow and red in 4b indicate Qof areas and blue circles indicate Qof delivery points. Variable width riparian forest buffer zones predicted by a LiDAR based groundwater hydrology model by Kuglerová et al. [82] (c,d). Panel 4c shows a sunlit LiDAR image of a stream section; blue lines are small streams and red stars are runoff collection points. In panel 4d, blue layers indicate model predicted groundwater discharge zones (darker blues indicate greater fluxes) and red areas are intermittent streams. All figures reproduced with permission.
Soilsystems 05 00015 g004aSoilsystems 05 00015 g004b
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Young, E.O.; Ross, D.S.; Jaisi, D.P.; Vidon, P.G. Phosphorus Transport along the Cropland–Riparian–Stream Continuum in Cold Climate Agroecosystems: A Review. Soil Syst. 2021, 5, 15. https://doi.org/10.3390/soilsystems5010015

AMA Style

Young EO, Ross DS, Jaisi DP, Vidon PG. Phosphorus Transport along the Cropland–Riparian–Stream Continuum in Cold Climate Agroecosystems: A Review. Soil Systems. 2021; 5(1):15. https://doi.org/10.3390/soilsystems5010015

Chicago/Turabian Style

Young, Eric O., Donald S. Ross, Deb P. Jaisi, and Philippe G. Vidon. 2021. "Phosphorus Transport along the Cropland–Riparian–Stream Continuum in Cold Climate Agroecosystems: A Review" Soil Systems 5, no. 1: 15. https://doi.org/10.3390/soilsystems5010015

Article Metrics

Back to TopTop